SSKG Hub: An Expert-Guided Platform for LLM-Empowered Sustainability Standards Knowledge Graphs
arXiv:2603.00669v1 Announce Type: new Abstract: Sustainability disclosure standards (e.g., GRI, SASB, TCFD, IFRS S2) are comprehensive yet lengthy, terminology-dense, and highly cross-referential, hindering structured analysis and downstream use. We present SSKG Hub (Sustainability Standards Knowledge Graph Hub), a research prototype and interactive web platform that transforms standards into auditable knowledge graphs (KGs) through an LLM-centered, expert-guided pipeline. The system integrates automatic standard identification, configurable chunking, standard-specific prompting, robust triple parsing, and provenance-aware Neo4j storage with fine-grained audit metadata. LLM extraction produces a provenance-linked Draft KG, which is reviewed, curated, and formally promoted to a Certified KG through meta-expert adjudication. A role-based governance framework covering read-only guest access, expert review and CRUD operations, meta-expert certification, and administrative oversight ensure
arXiv:2603.00669v1 Announce Type: new Abstract: Sustainability disclosure standards (e.g., GRI, SASB, TCFD, IFRS S2) are comprehensive yet lengthy, terminology-dense, and highly cross-referential, hindering structured analysis and downstream use. We present SSKG Hub (Sustainability Standards Knowledge Graph Hub), a research prototype and interactive web platform that transforms standards into auditable knowledge graphs (KGs) through an LLM-centered, expert-guided pipeline. The system integrates automatic standard identification, configurable chunking, standard-specific prompting, robust triple parsing, and provenance-aware Neo4j storage with fine-grained audit metadata. LLM extraction produces a provenance-linked Draft KG, which is reviewed, curated, and formally promoted to a Certified KG through meta-expert adjudication. A role-based governance framework covering read-only guest access, expert review and CRUD operations, meta-expert certification, and administrative oversight ensures traceability and accountability across draft and certified states. Beyond graph exploration and triple-level evidence tracing, SSKG Hub supports cross-KG fusion, KG-driven tasks, and dedicated modules for insights and curated resources. We validate the platform through a comprehensive expert-led KG review case study that demonstrates end-to-end curation and quality assurance. The web application is publicly available at www.sskg-hub.com.
Executive Summary
The article introduces SSKG Hub, a research prototype and interactive web platform that transforms sustainability disclosure standards into auditable knowledge graphs through an LLM-centered, expert-guided pipeline. The platform's robust architecture integrates automatic standard identification, configurable chunking, and provenance-aware storage, enabling meta-expert adjudication and role-based governance. The authors validate the platform through an expert-led KG review case study, demonstrating end-to-end curation and quality assurance. This innovative approach has significant implications for sustainability reporting, standardization, and knowledge management, facilitating structured analysis and downstream use of complex sustainability standards.
Key Points
- ▸ SSKG Hub presents an LLM-centered, expert-guided pipeline for transforming sustainability standards into auditable knowledge graphs.
- ▸ The platform integrates automatic standard identification, configurable chunking, and provenance-aware storage.
- ▸ SSKG Hub features a role-based governance framework ensuring traceability and accountability across draft and certified states.
Merits
Strength in innovative architecture
The integration of LLM extraction, expert guidance, and provenance-aware storage provides a robust and scalable architecture for knowledge graph construction.
Enhanced sustainability reporting
SSKG Hub's auditable knowledge graphs facilitate structured analysis and downstream use of complex sustainability standards, promoting improved reporting and decision-making.
Demerits
Potential complexity in LLM-centered pipeline
The reliance on LLM extraction may introduce complexity and require significant expertise, potentially limiting accessibility and usability.
Scalability and maintenance concerns
As the platform grows, concerns around scalability and maintenance may arise, requiring ongoing investment in infrastructure and expertise.
Expert Commentary
The introduction of SSKG Hub marks a significant advancement in the development of auditable knowledge graphs for sustainability standards. The innovative architecture and expert-guided pipeline demonstrate a clear understanding of the challenges associated with complex sustainability standards. While concerns around complexity and scalability exist, the potential benefits of improved reporting and regulation cannot be overstated. As the field continues to evolve, it will be essential to address these challenges and ensure the widespread adoption of auditable knowledge graphs. The expert-led review case study provides a valuable insight into the platform's capabilities and potential applications, highlighting the need for continued research and development in this area.
Recommendations
- ✓ Further investigation into the scalability and maintenance requirements of SSKG Hub, particularly in the context of growing user bases and increasing complexity.
- ✓ Exploration of potential applications beyond sustainability reporting, including standardization and regulatory frameworks, to fully realize the platform's potential.